Clinical Factors but Not Somatic Mutations Predict for Survival in Patients with Myelofibrosis Undergoing Allogeneic Hematopoietic Cell Transplant: Analysis of the North American Myelofibrosis Transplant Outcome (NAMTO) Study
Bibliographic record
Abstract
Introduction: Myelofibrosis (MF) is a clonal hematologic malignancy characterized by constitutive JAK-STAT activation and aberrant cytokine signaling. Allogeneic hematopoietic stem cell transplantation (allo-HCT) remains the only potentially curative therapy in MF. The contribution of disease-, patient- and donor-related factors to allo-HCT outcomes remains to be fully elucidated, as well as the presence of somatic mutations in genes such as ASXL1, EZH2, SRSF2, U2AF1 and IDH1/2 which are associated with worse prognosis in MF patients (pts). In this large multi- center retrospective analysis, we aimed to study the impact of clinical and molecular mutations on transplant outcomes. Methods: This analysis including 498 pts from 11 centers in North America and Canada. Univariate proportional-hazard Cox regression analysis stratified by center was used to assess the association of patient, transplant, and disease characteristics on overall survival (OS). Baseline patient demographic data and disease characteristics were selected as covariates in the multivariate analysis. Results: Pts transplanted between 2002-2021 were included in this analysis. Baseline and transplant characteristics are summarized in table 1. The 1- and 2-year OS was 77% (95% CI; 73-81) and 70% (95% CI; 66-74) and non-relapse mortality (NRM) 19% (95% CI: 17-21) and 23% (95% CI: 19-27), respectively. The cumulative incidence (CMI) of relapse at 1- and 2-years was 12% (95% CI; 10-14) and 16% (95% CI; 12-20). The CMI of acute graft versus host disease (aGVHD) grade II-IV was 31% (95% CI; 27-35) at 3 months and 42% (95% CI; 38-46) at 1-year post-transplant and grade was III-IV 13% (95% CI; 11-15) and 18% (95% CI; 14-22), respectively. The CMI of neutrophil engraftment at 1 and 3 months was 90% (95% CI: 87-93) and 97% (95% CI: 95-95) and for platelets 55% (95% CI: 50-59) and 80% (95% CI: 76-83). Univariate analysis included pts (age and gender), transplant (donor type and conditioning regimen intensity) and disease characteristics (DIPSS, mutations, cytogenetics (CG), blood counts, and spleen size). Hemoglobin > 10 g/dL (HR .5, 95% CI .34 -.73 p=3 x 10 -4) and platelets >50× 10 9/L (HR .59, 95% CI .42-.81, p=.0013) prior to transplant were associated with improved OS. High risk DIPSS was associated with decreased OS (p=0.0002). Mutations in ASXL1, EZH2, IDH1/2, U2AF1 and SRSF2 were not associated with decreased OS in this analysis (Figure 1). However, mutations in ZRSR2 were associated with inferior OS (HR 2.07, 95% CI 1.08-3.95, p=.0252). Lastly, JAK2 which had the most frequent mutations was not associated with OS (HR .0.93, 95% CI .65-1.31). There was no association between the CG risk groups and OS. Splenomegaly, measured radiographically, had no impact on OS but was strongly associated with engraftment (better engraftment defined as HR>1). For platelets, spleen size of 15.6-18.9 cm HR of 0.69 (95% CI .47-1, p=.0489) and size >18.9-22.5 cm HR of 0.48 ( 95% CI .33-.7, p=1x10^-4). For neutrophils, spleen size >19.9-22.5 cm had a HR of 0.68, (95% CI .48-.96, p=.0268) and size>22.5 cm had a HR of 0.65 (95% CI .46-.91, p=.0114). Mismatched unrelated (MMURD) and haplo identical donors had no impact on survival but were associated with delayed platelet engraftment; MMURD (HR .67, 95% CI .47-.96, p=.0298) and haploidentical donors (HR .56, 95% CI .39-.8, p=.0017). In a multivariate analysis adjusted for age, gender, highest DIPSS, donor type and conditioning regimen, platelets > 50× 10 9/L (HR .61, 95% CI .44-.87, p=.0053) hemoglobin >10 g/dL (HR .6, 95% CI .4-.9, p=.0244) and lower DIPSS at the time of transplant were associated with improved OS. Conclusions: In this large multicenter analysis only clinical variables; hemoglobin and platelets, were found to be associated with OS after allo-HCT in MF patients. Somatic mutations associated with poor prognosis were not associated with OS suggesting that transplant can overcome their negative impact. Splenomegaly was associated with delayed engraftment but not OS. Interestingly, using alternative donors (MMURD and haplo identical) didn't have a negative effect on OS, possibly reflecting the use of post-transplant cyclophosphamide for GVHD prophylaxis in recent years. These results highlight the importance of biologic factors in the prognostication of outcomes in MF pts undergoing allo-HCT independent of somatic mutations. Supported by the American Society of Hematology (ASH) and MPN Research Foundation
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".